Overview

Dataset statistics

Number of variables34
Number of observations13227011
Missing cells162792364
Missing cells (%)36.2%
Total size in memory3.4 GiB
Average record size in memory272.0 B

Variable types

Text27
Numeric7

Alerts

homedescription has 6351964 (48.0%) missing valuesMissing
neutraldescription has 12914970 (97.6%) missing valuesMissing
visitordescription has 6455244 (48.8%) missing valuesMissing
score has 9759243 (73.8%) missing valuesMissing
scoremargin has 9759243 (73.8%) missing valuesMissing
player1_name has 1178896 (8.9%) missing valuesMissing
player1_team_id has 1187147 (9.0%) missing valuesMissing
player1_team_city has 1187147 (9.0%) missing valuesMissing
player1_team_nickname has 1187147 (9.0%) missing valuesMissing
player1_team_abbreviation has 1187147 (9.0%) missing valuesMissing
player2_name has 9454004 (71.5%) missing valuesMissing
player2_team_id has 9430400 (71.3%) missing valuesMissing
player2_team_city has 9430400 (71.3%) missing valuesMissing
player2_team_nickname has 9430400 (71.3%) missing valuesMissing
player2_team_abbreviation has 9430400 (71.3%) missing valuesMissing
player3_name has 12893043 (97.5%) missing valuesMissing
player3_team_id has 12888166 (97.4%) missing valuesMissing
player3_team_city has 12888166 (97.4%) missing valuesMissing
player3_team_nickname has 12888166 (97.4%) missing valuesMissing
player3_team_abbreviation has 12888166 (97.4%) missing valuesMissing
eventmsgactiontype has 4302057 (32.5%) zerosZeros
person1type has 259913 (2.0%) zerosZeros
person2type has 9429986 (71.3%) zerosZeros
person3type has 11439649 (86.5%) zerosZeros

Reproduction

Analysis started2023-06-27 09:29:22.178806
Analysis finished2023-06-27 11:16:08.129327
Duration1 hour, 46 minutes and 45.95 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

Distinct29094
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:10.235358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters132270110
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0029600009
2nd row0029600009
3rd row0029600009
4th row0029600009
5th row0029600009
ValueCountFrequency (%)
0029700110 709
 
< 0.1%
0021500391 707
 
< 0.1%
0021800928 694
 
< 0.1%
0021600711 691
 
< 0.1%
0029800100 686
 
< 0.1%
0029900004 677
 
< 0.1%
0021100722 653
 
< 0.1%
0021000925 653
 
< 0.1%
0029900985 646
 
< 0.1%
0020600010 643
 
< 0.1%
Other values (29084) 13220252
99.9%
2023-06-27T19:16:10.659200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62404589
47.2%
2 20221542
 
15.3%
1 12887389
 
9.7%
9 7049211
 
5.3%
6 5332578
 
4.0%
8 5098397
 
3.9%
5 4852854
 
3.7%
4 4838690
 
3.7%
3 4824530
 
3.6%
7 4760330
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 132270110
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62404589
47.2%
2 20221542
 
15.3%
1 12887389
 
9.7%
9 7049211
 
5.3%
6 5332578
 
4.0%
8 5098397
 
3.9%
5 4852854
 
3.7%
4 4838690
 
3.7%
3 4824530
 
3.6%
7 4760330
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 132270110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62404589
47.2%
2 20221542
 
15.3%
1 12887389
 
9.7%
9 7049211
 
5.3%
6 5332578
 
4.0%
8 5098397
 
3.9%
5 4852854
 
3.7%
4 4838690
 
3.7%
3 4824530
 
3.6%
7 4760330
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132270110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62404589
47.2%
2 20221542
 
15.3%
1 12887389
 
9.7%
9 7049211
 
5.3%
6 5332578
 
4.0%
8 5098397
 
3.9%
5 4852854
 
3.7%
4 4838690
 
3.7%
3 4824530
 
3.6%
7 4760330
 
3.6%

eventnum
Real number (ℝ)

Distinct986
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean267.6273325
Minimum0
Maximum1018
Zeros21853
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:10.741960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25
Q1129
median262
Q3394
95-th percentile540
Maximum1018
Range1018
Interquartile range (IQR)265

Descriptive statistics

Standard deviation163.4640928
Coefficient of variation (CV)0.6107899789
Kurtosis-0.742295422
Mean267.6273325
Median Absolute Deviation (MAD)132
Skewness0.2636801232
Sum3539909671
Variance26720.50963
MonotonicityNot monotonic
2023-06-27T19:16:10.821805image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 28345
 
0.2%
2 28184
 
0.2%
7 27923
 
0.2%
9 27392
 
0.2%
11 27010
 
0.2%
13 26695
 
0.2%
15 26578
 
0.2%
17 26521
 
0.2%
16 26479
 
0.2%
12 26386
 
0.2%
Other values (976) 12955498
97.9%
ValueCountFrequency (%)
0 21853
0.2%
1 23115
0.2%
2 28184
0.2%
3 23241
0.2%
4 28345
0.2%
ValueCountFrequency (%)
1018 1
< 0.1%
1016 1
< 0.1%
1014 1
< 0.1%
1013 1
< 0.1%
1012 1
< 0.1%

eventmsgtype
Real number (ℝ)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.972313624
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:10.908221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile9
Maximum18
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.613288568
Coefficient of variation (CV)0.6578756905
Kurtosis2.066605785
Mean3.972313624
Median Absolute Deviation (MAD)2
Skewness1.227054833
Sum52541836
Variance6.82927714
MonotonicityNot monotonic
2023-06-27T19:16:10.959310image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 2968800
22.4%
2 2626835
19.9%
1 2182176
16.5%
3 1405950
10.6%
6 1270290
9.6%
8 1183307
 
8.9%
5 847769
 
6.4%
9 375131
 
2.8%
13 118504
 
0.9%
12 118268
 
0.9%
Other values (4) 129981
 
1.0%
ValueCountFrequency (%)
1 2182176
16.5%
2 2626835
19.9%
3 1405950
10.6%
4 2968800
22.4%
5 847769
 
6.4%
ValueCountFrequency (%)
18 25476
 
0.2%
13 118504
0.9%
12 118268
0.9%
11 1902
 
< 0.1%
10 50747
0.4%

eventmsgactiontype
Real number (ℝ)

ZEROS 

Distinct108
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.813976491
Minimum0
Maximum110
Zeros4302057
Zeros (%)32.5%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:11.025785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile63
Maximum110
Range110
Interquartile range (IQR)5

Descriptive statistics

Standard deviation19.98788148
Coefficient of variation (CV)2.267748444
Kurtosis8.424260384
Mean8.813976491
Median Absolute Deviation (MAD)1
Skewness3.002197542
Sum116582564
Variance399.5154059
MonotonicityNot monotonic
2023-06-27T19:16:11.097763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4302057
32.5%
1 3759558
28.4%
2 851779
 
6.4%
5 702312
 
5.3%
11 654499
 
4.9%
12 598876
 
4.5%
4 258257
 
2.0%
3 180014
 
1.4%
42 177612
 
1.3%
79 171659
 
1.3%
Other values (98) 1570388
 
11.9%
ValueCountFrequency (%)
0 4302057
32.5%
1 3759558
28.4%
2 851779
 
6.4%
3 180014
 
1.4%
4 258257
 
2.0%
ValueCountFrequency (%)
110 129
 
< 0.1%
109 261
 
< 0.1%
108 17507
0.1%
107 3800
 
< 0.1%
106 1427
 
< 0.1%

period
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.550352003
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:11.150863image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.140323581
Coefficient of variation (CV)0.4471239967
Kurtosis-1.200806667
Mean2.550352003
Median Absolute Deviation (MAD)1
Skewness0.03932032232
Sum33733534
Variance1.300337868
MonotonicityNot monotonic
2023-06-27T19:16:11.196737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 3431863
25.9%
2 3371976
25.5%
3 3180641
24.0%
1 3127811
23.6%
5 98572
 
0.7%
6 13812
 
0.1%
7 2024
 
< 0.1%
8 312
 
< 0.1%
ValueCountFrequency (%)
1 3127811
23.6%
2 3371976
25.5%
3 3180641
24.0%
4 3431863
25.9%
5 98572
 
0.7%
ValueCountFrequency (%)
8 312
 
< 0.1%
7 2024
 
< 0.1%
6 13812
 
0.1%
5 98572
 
0.7%
4 3431863
25.9%
Distinct3993
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:11.448822image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.360674985
Min length0

Characters and Unicode

Total characters97359729
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)< 0.1%

Sample

1st row11:44 PM
2nd row11:45 PM
3rd row11:46 PM
4th row11:46 PM
5th row11:46 PM
ValueCountFrequency (%)
pm 12373258
46.8%
am 851478
 
3.2%
9:01 53580
 
0.2%
9:00 53539
 
0.2%
9:03 53528
 
0.2%
9:02 53131
 
0.2%
8:59 53028
 
0.2%
8:58 52495
 
0.2%
9:04 52451
 
0.2%
8:57 52274
 
0.2%
Other values (2871) 12802947
48.4%
2023-06-27T19:16:11.758248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 13226061
13.6%
13225648
13.6%
M 13224736
13.6%
P 12373258
12.7%
1 10177554
10.5%
2 5300003
5.4%
0 5209780
 
5.4%
3 4070574
 
4.2%
9 3991061
 
4.1%
4 3905191
 
4.0%
Other values (6) 12655863
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44452909
45.7%
Uppercase Letter 26450384
27.2%
Other Punctuation 13226061
 
13.6%
Space Separator 13225648
 
13.6%
Dash Punctuation 4727
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10177554
22.9%
2 5300003
11.9%
0 5209780
11.7%
3 4070574
 
9.2%
9 3991061
 
9.0%
4 3905191
 
8.8%
5 3815716
 
8.6%
8 3806754
 
8.6%
7 2617210
 
5.9%
6 1559066
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
M 13224736
50.0%
P 12373258
46.8%
A 852390
 
3.2%
Other Punctuation
ValueCountFrequency (%)
: 13226061
100.0%
Space Separator
ValueCountFrequency (%)
13225648
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4727
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70909345
72.8%
Latin 26450384
 
27.2%

Most frequent character per script

Common
ValueCountFrequency (%)
: 13226061
18.7%
13225648
18.7%
1 10177554
14.4%
2 5300003
7.5%
0 5209780
 
7.3%
3 4070574
 
5.7%
9 3991061
 
5.6%
4 3905191
 
5.5%
5 3815716
 
5.4%
8 3806754
 
5.4%
Other values (3) 4181003
 
5.9%
Latin
ValueCountFrequency (%)
M 13224736
50.0%
P 12373258
46.8%
A 852390
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97359729
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 13226061
13.6%
13225648
13.6%
M 13224736
13.6%
P 12373258
12.7%
1 10177554
10.5%
2 5300003
5.4%
0 5209780
 
5.4%
3 4070574
 
4.2%
9 3991061
 
4.1%
4 3905191
 
4.0%
Other values (6) 12655863
13.0%
Distinct721
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:12.095736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.139076016
Min length4

Characters and Unicode

Total characters54747604
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12:00
2nd row12:00
3rd row11:49
4th row11:27
5th row11:23
ValueCountFrequency (%)
0:00 276749
 
2.1%
12:00 146948
 
1.1%
0:01 56236
 
0.4%
0:02 42509
 
0.3%
0:03 36681
 
0.3%
0:04 32377
 
0.2%
0:05 28924
 
0.2%
0:30 26662
 
0.2%
0:31 26640
 
0.2%
0:06 26493
 
0.2%
Other values (711) 12526792
94.7%
2023-06-27T19:16:12.483737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 13227011
24.2%
1 7129326
13.0%
0 6927949
12.7%
2 4745786
 
8.7%
3 4559163
 
8.3%
4 4529013
 
8.3%
5 4390096
 
8.0%
6 2350605
 
4.3%
7 2313013
 
4.2%
8 2308824
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41520593
75.8%
Other Punctuation 13227011
 
24.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7129326
17.2%
0 6927949
16.7%
2 4745786
11.4%
3 4559163
11.0%
4 4529013
10.9%
5 4390096
10.6%
6 2350605
 
5.7%
7 2313013
 
5.6%
8 2308824
 
5.6%
9 2266818
 
5.5%
Other Punctuation
ValueCountFrequency (%)
: 13227011
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54747604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 13227011
24.2%
1 7129326
13.0%
0 6927949
12.7%
2 4745786
 
8.7%
3 4559163
 
8.3%
4 4529013
 
8.3%
5 4390096
 
8.0%
6 2350605
 
4.3%
7 2313013
 
4.2%
8 2308824
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54747604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 13227011
24.2%
1 7129326
13.0%
0 6927949
12.7%
2 4745786
 
8.7%
3 4559163
 
8.3%
4 4529013
 
8.3%
5 4390096
 
8.0%
6 2350605
 
4.3%
7 2313013
 
4.2%
8 2308824
 
4.2%

homedescription
Text

MISSING 

Distinct1753685
Distinct (%)25.5%
Missing6351964
Missing (%)48.0%
Memory size100.9 MiB
2023-06-27T19:16:15.310487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length81
Median length72
Mean length29.64946887
Min length0

Characters and Unicode

Total characters203841492
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1301733 ?
Unique (%)18.9%

Sample

1st rowJump Ball Olajuwon vs. Polynice: Tip to Williamson
2nd rowMISS Olajuwon 13' Jump Shot
3rd rowDrexler REBOUND (Off:1 Def:0)
4th rowMISS Drexler Layup
5th rowOlajuwon REBOUND (Off:1 Def:0)
ValueCountFrequency (%)
shot 1707937
 
4.7%
pts 1648408
 
4.5%
jump 1577175
 
4.3%
2 1557130
 
4.3%
rebound 1504994
 
4.1%
miss 1474263
 
4.0%
1 1165248
 
3.2%
of 736062
 
2.0%
throw 716310
 
2.0%
free 716310
 
2.0%
Other values (2389) 23787541
65.0%
2023-06-27T19:16:15.744788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30069023
 
14.8%
S 9562201
 
4.7%
o 9061736
 
4.4%
e 8589174
 
4.2%
r 7219692
 
3.5%
T 6229415
 
3.1%
a 6066156
 
3.0%
n 5634308
 
2.8%
u 5378048
 
2.6%
) 5318096
 
2.6%
Other values (60) 110713643
54.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 84418023
41.4%
Uppercase Letter 57737576
28.3%
Space Separator 30069023
 
14.8%
Decimal Number 13466729
 
6.6%
Other Punctuation 7425442
 
3.6%
Close Punctuation 5318096
 
2.6%
Open Punctuation 5318096
 
2.6%
Dash Punctuation 88507
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 9061736
 
10.7%
e 8589174
 
10.2%
r 7219692
 
8.6%
a 6066156
 
7.2%
n 5634308
 
6.7%
u 5378048
 
6.4%
f 4870286
 
5.8%
l 4697322
 
5.6%
i 4438328
 
5.3%
t 4358776
 
5.2%
Other values (16) 24104197
28.6%
Uppercase Letter
ValueCountFrequency (%)
S 9562201
16.6%
T 6229415
10.8%
P 4464083
 
7.7%
O 4226768
 
7.3%
B 3542960
 
6.1%
D 3457682
 
6.0%
R 3126392
 
5.4%
F 2599608
 
4.5%
U 2502804
 
4.3%
L 2493284
 
4.3%
Other values (15) 15532379
26.9%
Decimal Number
ValueCountFrequency (%)
1 3961650
29.4%
2 3394090
25.2%
3 1733565
12.9%
0 989090
 
7.3%
4 938828
 
7.0%
5 716384
 
5.3%
6 614034
 
4.6%
7 442030
 
3.3%
8 373957
 
2.8%
9 303101
 
2.3%
Other Punctuation
ValueCountFrequency (%)
: 3363768
45.3%
. 2067545
27.8%
' 1976053
26.6%
# 17885
 
0.2%
, 191
 
< 0.1%
Space Separator
ValueCountFrequency (%)
30069023
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5318096
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5318096
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88507
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 142155599
69.7%
Common 61685893
30.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 9562201
 
6.7%
o 9061736
 
6.4%
e 8589174
 
6.0%
r 7219692
 
5.1%
T 6229415
 
4.4%
a 6066156
 
4.3%
n 5634308
 
4.0%
u 5378048
 
3.8%
f 4870286
 
3.4%
l 4697322
 
3.3%
Other values (41) 74847261
52.7%
Common
ValueCountFrequency (%)
30069023
48.7%
) 5318096
 
8.6%
( 5318096
 
8.6%
1 3961650
 
6.4%
2 3394090
 
5.5%
: 3363768
 
5.5%
. 2067545
 
3.4%
' 1976053
 
3.2%
3 1733565
 
2.8%
0 989090
 
1.6%
Other values (9) 3494917
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203841492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30069023
 
14.8%
S 9562201
 
4.7%
o 9061736
 
4.4%
e 8589174
 
4.2%
r 7219692
 
3.5%
T 6229415
 
3.1%
a 6066156
 
3.0%
n 5634308
 
2.8%
u 5378048
 
2.6%
) 5318096
 
2.6%
Other values (60) 110713643
54.3%

neutraldescription
Text

MISSING 

Distinct18051
Distinct (%)5.8%
Missing12914970
Missing (%)97.6%
Memory size100.9 MiB
2023-06-27T19:16:16.115885image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length77
Median length73
Mean length29.90817232
Min length0

Characters and Unicode

Total characters9332576
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8294 ?
Unique (%)2.7%

Sample

1st rowStart of 1st Period (11:44 PM EST)
2nd rowEnd of 1st Period (12:07 PM EST)
3rd rowStart of 2nd Period (12:10 PM EST)
4th rowEnd of 2nd Period (12:37 PM EST)
5th rowStart of 3rd Period (12:53 PM EST)
ValueCountFrequency (%)
est 250557
13.2%
period 246050
13.0%
of 237238
12.5%
pm 235355
12.4%
end 118500
 
6.3%
start 118237
 
6.3%
1st 61567
 
3.3%
2nd 58706
 
3.1%
3rd 58280
 
3.1%
4th 58184
 
3.1%
Other values (2668) 448530
23.7%
2023-06-27T19:16:16.520109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1580641
16.9%
o 552642
 
5.9%
d 491230
 
5.3%
P 486753
 
5.2%
r 454068
 
4.9%
t 448251
 
4.8%
i 383175
 
4.1%
S 380238
 
4.1%
E 369887
 
4.0%
e 326306
 
3.5%
Other values (59) 3859385
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3890996
41.7%
Uppercase Letter 1944781
20.8%
Space Separator 1580641
16.9%
Decimal Number 1094688
 
11.7%
Other Punctuation 307701
 
3.3%
Open Punctuation 254945
 
2.7%
Close Punctuation 254945
 
2.7%
Dash Punctuation 3879
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 552642
14.2%
d 491230
12.6%
r 454068
11.7%
t 448251
11.5%
i 383175
9.8%
e 326306
8.4%
f 311838
8.0%
n 235339
6.0%
a 200327
 
5.1%
l 87702
 
2.3%
Other values (16) 400118
10.3%
Uppercase Letter
ValueCountFrequency (%)
P 486753
25.0%
S 380238
19.6%
E 369887
19.0%
T 305059
15.7%
M 252596
13.0%
O 49117
 
2.5%
R 30401
 
1.6%
A 16088
 
0.8%
I 14069
 
0.7%
F 13794
 
0.7%
Other values (15) 26779
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 267384
24.4%
2 155247
14.2%
3 142397
13.0%
4 138720
12.7%
0 99711
 
9.1%
9 75946
 
6.9%
8 75799
 
6.9%
5 63170
 
5.8%
7 46934
 
4.3%
6 29380
 
2.7%
Other Punctuation
ValueCountFrequency (%)
: 297492
96.7%
. 6335
 
2.1%
, 3679
 
1.2%
' 195
 
0.1%
Space Separator
ValueCountFrequency (%)
1580641
100.0%
Open Punctuation
ValueCountFrequency (%)
( 254945
100.0%
Close Punctuation
ValueCountFrequency (%)
) 254945
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3879
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5835777
62.5%
Common 3496799
37.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 552642
 
9.5%
d 491230
 
8.4%
P 486753
 
8.3%
r 454068
 
7.8%
t 448251
 
7.7%
i 383175
 
6.6%
S 380238
 
6.5%
E 369887
 
6.3%
e 326306
 
5.6%
f 311838
 
5.3%
Other values (41) 1631389
28.0%
Common
ValueCountFrequency (%)
1580641
45.2%
: 297492
 
8.5%
1 267384
 
7.6%
( 254945
 
7.3%
) 254945
 
7.3%
2 155247
 
4.4%
3 142397
 
4.1%
4 138720
 
4.0%
0 99711
 
2.9%
9 75946
 
2.2%
Other values (8) 229371
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9332576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1580641
16.9%
o 552642
 
5.9%
d 491230
 
5.3%
P 486753
 
5.2%
r 454068
 
4.9%
t 448251
 
4.8%
i 383175
 
4.1%
S 380238
 
4.1%
E 369887
 
4.0%
e 326306
 
3.5%
Other values (59) 3859385
41.4%

visitordescription
Text

MISSING 

Distinct1702020
Distinct (%)25.1%
Missing6455244
Missing (%)48.8%
Memory size100.9 MiB
2023-06-27T19:16:18.788283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length84
Median length75
Mean length29.40092844
Min length0

Characters and Unicode

Total characters199096237
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1246368 ?
Unique (%)18.4%

Sample

1st rowWilliamson Traveling Turnover (P1.T1)
2nd rowAbdul-Rauf 9' Jump Shot (2 PTS)
3rd rowMISS Williamson 13' Jump Shot
4th rowPolynice REBOUND (Off:1 Def:0)
5th rowWilliamson Layup (2 PTS) (Polynice 1 AST)
ValueCountFrequency (%)
shot 1735891
 
4.9%
pts 1597681
 
4.5%
jump 1561249
 
4.4%
miss 1494513
 
4.2%
2 1468069
 
4.1%
rebound 1463793
 
4.1%
1 1098553
 
3.1%
of 710731
 
2.0%
throw 689638
 
1.9%
free 689638
 
1.9%
Other values (2400) 23037314
64.8%
2023-06-27T19:16:19.195904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29105836
 
14.6%
S 9122413
 
4.6%
o 8975903
 
4.5%
e 8799345
 
4.4%
r 7323284
 
3.7%
a 6089808
 
3.1%
T 5938954
 
3.0%
n 5579134
 
2.8%
u 5226101
 
2.6%
) 5196296
 
2.6%
Other values (60) 107739163
54.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 84480522
42.4%
Uppercase Letter 54264555
27.3%
Space Separator 29105836
 
14.6%
Decimal Number 13280126
 
6.7%
Other Punctuation 7487188
 
3.8%
Close Punctuation 5196296
 
2.6%
Open Punctuation 5196296
 
2.6%
Dash Punctuation 85418
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 8975903
 
10.6%
e 8799345
 
10.4%
r 7323284
 
8.7%
a 6089808
 
7.2%
n 5579134
 
6.6%
u 5226101
 
6.2%
f 4711713
 
5.6%
i 4470560
 
5.3%
t 4412378
 
5.2%
l 4297922
 
5.1%
Other values (16) 24594374
29.1%
Uppercase Letter
ValueCountFrequency (%)
S 9122413
16.8%
T 5938954
10.9%
P 4369911
 
8.1%
O 4037424
 
7.4%
B 3387081
 
6.2%
D 3307519
 
6.1%
R 2976900
 
5.5%
F 2423976
 
4.5%
U 2396510
 
4.4%
L 2313065
 
4.3%
Other values (15) 13990802
25.8%
Decimal Number
ValueCountFrequency (%)
1 3914471
29.5%
2 3338000
25.1%
3 1715101
12.9%
0 980767
 
7.4%
4 922397
 
6.9%
5 700734
 
5.3%
6 603046
 
4.5%
7 435789
 
3.3%
8 368847
 
2.8%
9 300974
 
2.3%
Other Punctuation
ValueCountFrequency (%)
: 3245725
43.4%
. 2225315
29.7%
' 1997201
26.7%
# 18794
 
0.3%
, 153
 
< 0.1%
Space Separator
ValueCountFrequency (%)
29105836
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5196296
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5196296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85418
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 138745077
69.7%
Common 60351160
30.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 9122413
 
6.6%
o 8975903
 
6.5%
e 8799345
 
6.3%
r 7323284
 
5.3%
a 6089808
 
4.4%
T 5938954
 
4.3%
n 5579134
 
4.0%
u 5226101
 
3.8%
f 4711713
 
3.4%
i 4470560
 
3.2%
Other values (41) 72507862
52.3%
Common
ValueCountFrequency (%)
29105836
48.2%
) 5196296
 
8.6%
( 5196296
 
8.6%
1 3914471
 
6.5%
2 3338000
 
5.5%
: 3245725
 
5.4%
. 2225315
 
3.7%
' 1997201
 
3.3%
3 1715101
 
2.8%
0 980767
 
1.6%
Other values (9) 3436152
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 199096237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29105836
 
14.6%
S 9122413
 
4.6%
o 8975903
 
4.5%
e 8799345
 
4.4%
r 7323284
 
3.7%
a 6089808
 
3.1%
T 5938954
 
3.0%
n 5579134
 
2.8%
u 5226101
 
2.6%
) 5196296
 
2.6%
Other values (60) 107739163
54.1%

score
Text

MISSING 

Distinct11184
Distinct (%)0.3%
Missing9759243
Missing (%)73.8%
Memory size100.9 MiB
2023-06-27T19:16:19.501980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.970017314
Min length5

Characters and Unicode

Total characters24170403
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1116 ?
Unique (%)< 0.1%

Sample

1st row0 - 2
2nd row2 - 2
3rd row2 - 4
4th row4 - 4
5th row6 - 4
ValueCountFrequency (%)
3467768
33.3%
2 98897
 
1.0%
4 81677
 
0.8%
6 72570
 
0.7%
25 72359
 
0.7%
23 71909
 
0.7%
24 71846
 
0.7%
26 71627
 
0.7%
27 71601
 
0.7%
22 71600
 
0.7%
Other values (167) 6251450
60.1%
2023-06-27T19:16:19.804169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6935536
28.7%
- 3467768
14.3%
1 1890860
 
7.8%
2 1505619
 
6.2%
4 1422094
 
5.9%
6 1392339
 
5.8%
5 1377233
 
5.7%
3 1361910
 
5.6%
7 1359930
 
5.6%
8 1308502
 
5.4%
Other values (2) 2148612
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13767099
57.0%
Space Separator 6935536
28.7%
Dash Punctuation 3467768
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1890860
13.7%
2 1505619
10.9%
4 1422094
10.3%
6 1392339
10.1%
5 1377233
10.0%
3 1361910
9.9%
7 1359930
9.9%
8 1308502
9.5%
9 1146076
8.3%
0 1002536
7.3%
Space Separator
ValueCountFrequency (%)
6935536
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3467768
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24170403
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6935536
28.7%
- 3467768
14.3%
1 1890860
 
7.8%
2 1505619
 
6.2%
4 1422094
 
5.9%
6 1392339
 
5.8%
5 1377233
 
5.7%
3 1361910
 
5.6%
7 1359930
 
5.6%
8 1308502
 
5.4%
Other values (2) 2148612
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24170403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6935536
28.7%
- 3467768
14.3%
1 1890860
 
7.8%
2 1505619
 
6.2%
4 1422094
 
5.9%
6 1392339
 
5.8%
5 1377233
 
5.7%
3 1361910
 
5.6%
7 1359930
 
5.6%
8 1308502
 
5.4%
Other values (2) 2148612
 
8.9%

scoremargin
Text

MISSING 

Distinct142
Distinct (%)< 0.1%
Missing9759243
Missing (%)73.8%
Memory size100.9 MiB
2023-06-27T19:16:19.929181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.831058767
Min length1

Characters and Unicode

Total characters6349687
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st row2
2nd rowTIE
3rd row2
4th rowTIE
5th row-2
ValueCountFrequency (%)
2 324924
 
9.4%
1 299400
 
8.6%
3 281060
 
8.1%
4 266326
 
7.7%
5 241405
 
7.0%
6 222089
 
6.4%
7 200748
 
5.8%
8 181319
 
5.2%
tie 167441
 
4.8%
9 161391
 
4.7%
Other values (67) 1121665
32.3%
2023-06-27T19:16:20.126330image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1425372
22.4%
1 1333225
21.0%
2 684665
10.8%
3 446934
 
7.0%
4 383482
 
6.0%
5 339675
 
5.3%
6 306873
 
4.8%
7 274308
 
4.3%
8 245362
 
3.9%
9 216489
 
3.4%
Other values (4) 693302
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4421992
69.6%
Dash Punctuation 1425372
 
22.4%
Uppercase Letter 502323
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1333225
30.1%
2 684665
15.5%
3 446934
 
10.1%
4 383482
 
8.7%
5 339675
 
7.7%
6 306873
 
6.9%
7 274308
 
6.2%
8 245362
 
5.5%
9 216489
 
4.9%
0 190979
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
T 167441
33.3%
I 167441
33.3%
E 167441
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1425372
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5847364
92.1%
Latin 502323
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1425372
24.4%
1 1333225
22.8%
2 684665
11.7%
3 446934
 
7.6%
4 383482
 
6.6%
5 339675
 
5.8%
6 306873
 
5.2%
7 274308
 
4.7%
8 245362
 
4.2%
9 216489
 
3.7%
Latin
ValueCountFrequency (%)
T 167441
33.3%
I 167441
33.3%
E 167441
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6349687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1425372
22.4%
1 1333225
21.0%
2 684665
10.8%
3 446934
 
7.0%
4 383482
 
6.0%
5 339675
 
5.3%
6 306873
 
4.8%
7 274308
 
4.3%
8 245362
 
3.9%
9 216489
 
3.4%
Other values (4) 693302
10.9%

person1type
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)< 0.1%
Missing2905
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4.265308143
Minimum0
Maximum7
Zeros259913
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:20.185663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median4
Q35
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9444022502
Coefficient of variation (CV)0.2214147768
Kurtosis7.005859061
Mean4.265308143
Median Absolute Deviation (MAD)1
Skewness-2.266954084
Sum56404887
Variance0.8918956102
MonotonicityNot monotonic
2023-06-27T19:16:20.230088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 6064991
45.9%
5 5974873
45.2%
3 440619
 
3.3%
2 438157
 
3.3%
0 259913
 
2.0%
1 40702
 
0.3%
7 2579
 
< 0.1%
6 2272
 
< 0.1%
(Missing) 2905
 
< 0.1%
ValueCountFrequency (%)
0 259913
 
2.0%
1 40702
 
0.3%
2 438157
 
3.3%
3 440619
 
3.3%
4 6064991
45.9%
ValueCountFrequency (%)
7 2579
 
< 0.1%
6 2272
 
< 0.1%
5 5974873
45.2%
4 6064991
45.9%
3 440619
 
3.3%
Distinct3270
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:20.586267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length7
Mean length5.029730148
Min length1

Characters and Unicode

Total characters66528296
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row165
3rd row722
4th row165
5th row17
ValueCountFrequency (%)
0 282670
 
2.1%
2544 53885
 
0.4%
1495 52757
 
0.4%
1717 51331
 
0.4%
977 51164
 
0.4%
708 49522
 
0.4%
1718 44447
 
0.3%
2546 43229
 
0.3%
2730 42873
 
0.3%
1713 41866
 
0.3%
Other values (3260) 12513267
94.6%
2023-06-27T19:16:20.974252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12116750
18.2%
2 11831643
17.8%
0 9132508
13.7%
6 6773368
10.2%
7 5483544
8.2%
3 4722477
 
7.1%
9 4568779
 
6.9%
5 4252081
 
6.4%
4 4169450
 
6.3%
8 3477696
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66528296
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12116750
18.2%
2 11831643
17.8%
0 9132508
13.7%
6 6773368
10.2%
7 5483544
8.2%
3 4722477
 
7.1%
9 4568779
 
6.9%
5 4252081
 
6.4%
4 4169450
 
6.3%
8 3477696
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 66528296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12116750
18.2%
2 11831643
17.8%
0 9132508
13.7%
6 6773368
10.2%
7 5483544
8.2%
3 4722477
 
7.1%
9 4568779
 
6.9%
5 4252081
 
6.4%
4 4169450
 
6.3%
8 3477696
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66528296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12116750
18.2%
2 11831643
17.8%
0 9132508
13.7%
6 6773368
10.2%
7 5483544
8.2%
3 4722477
 
7.1%
9 4568779
 
6.9%
5 4252081
 
6.4%
4 4169450
 
6.3%
8 3477696
 
5.2%

player1_name
Text

MISSING 

Distinct2531
Distinct (%)< 0.1%
Missing1178896
Missing (%)8.9%
Memory size100.9 MiB
2023-06-27T19:16:21.243337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.81917312
Min length4

Characters and Unicode

Total characters154446872
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowHakeem Olajuwon
2nd rowCorliss Williamson
3rd rowHakeem Olajuwon
4th rowClyde Drexler
5th rowClyde Drexler
ValueCountFrequency (%)
williams 224819
 
0.9%
chris 223197
 
0.9%
kevin 175822
 
0.7%
anthony 163400
 
0.7%
jason 159505
 
0.7%
james 156416
 
0.6%
johnson 141845
 
0.6%
michael 140541
 
0.6%
davis 139193
 
0.6%
paul 131530
 
0.5%
Other values (2738) 22654625
93.2%
2023-06-27T19:16:21.577209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 13067685
 
8.5%
a 12654885
 
8.2%
12262778
 
7.9%
n 11348575
 
7.3%
r 11039848
 
7.1%
o 10139457
 
6.6%
i 8926366
 
5.8%
l 7672712
 
5.0%
s 6571035
 
4.3%
t 4589134
 
3.0%
Other values (46) 56174397
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 116078995
75.2%
Uppercase Letter 25405642
 
16.4%
Space Separator 12262778
 
7.9%
Other Punctuation 559204
 
0.4%
Dash Punctuation 140253
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13067685
11.3%
a 12654885
10.9%
n 11348575
9.8%
r 11039848
9.5%
o 10139457
 
8.7%
i 8926366
 
7.7%
l 7672712
 
6.6%
s 6571035
 
5.7%
t 4589134
 
4.0%
d 3752752
 
3.2%
Other values (16) 26316546
22.7%
Uppercase Letter
ValueCountFrequency (%)
J 2490458
 
9.8%
M 2286027
 
9.0%
D 1983807
 
7.8%
B 1865424
 
7.3%
A 1632546
 
6.4%
C 1626852
 
6.4%
S 1490418
 
5.9%
R 1470893
 
5.8%
T 1248116
 
4.9%
G 1174049
 
4.6%
Other values (16) 8137052
32.0%
Other Punctuation
ValueCountFrequency (%)
. 392456
70.2%
' 166748
29.8%
Space Separator
ValueCountFrequency (%)
12262778
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140253
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 141484637
91.6%
Common 12962235
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13067685
 
9.2%
a 12654885
 
8.9%
n 11348575
 
8.0%
r 11039848
 
7.8%
o 10139457
 
7.2%
i 8926366
 
6.3%
l 7672712
 
5.4%
s 6571035
 
4.6%
t 4589134
 
3.2%
d 3752752
 
2.7%
Other values (42) 51722188
36.6%
Common
ValueCountFrequency (%)
12262778
94.6%
. 392456
 
3.0%
' 166748
 
1.3%
- 140253
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 154446872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 13067685
 
8.5%
a 12654885
 
8.2%
12262778
 
7.9%
n 11348575
 
7.3%
r 11039848
 
7.1%
o 10139457
 
6.6%
i 8926366
 
5.8%
l 7672712
 
5.0%
s 6571035
 
4.3%
t 4589134
 
3.0%
Other values (46) 56174397
36.4%

player1_team_id
Text

MISSING 

Distinct30
Distinct (%)< 0.1%
Missing1187147
Missing (%)9.0%
Memory size100.9 MiB
2023-06-27T19:16:21.785688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters144478368
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1610612745.0
2nd row1610612758.0
3rd row1610612745.0
4th row1610612745.0
5th row1610612745.0
ValueCountFrequency (%)
1610612744.0 413778
 
3.4%
1610612747.0 413506
 
3.4%
1610612743.0 413124
 
3.4%
1610612755.0 411972
 
3.4%
1610612738.0 411430
 
3.4%
1610612760.0 409396
 
3.4%
1610612758.0 408581
 
3.4%
1610612764.0 408263
 
3.4%
1610612754.0 407595
 
3.4%
1610612751.0 407526
 
3.4%
Other values (20) 7934693
65.9%
2023-06-27T19:16:22.026513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 37332889
25.8%
6 28052632
19.4%
0 25205595
17.4%
7 13259868
 
9.2%
2 13250388
 
9.2%
. 12039864
 
8.3%
5 5265686
 
3.6%
4 5202500
 
3.6%
3 2440907
 
1.7%
8 1214301
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 132438504
91.7%
Other Punctuation 12039864
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37332889
28.2%
6 28052632
21.2%
0 25205595
19.0%
7 13259868
 
10.0%
2 13250388
 
10.0%
5 5265686
 
4.0%
4 5202500
 
3.9%
3 2440907
 
1.8%
8 1214301
 
0.9%
9 1213738
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 12039864
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 144478368
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37332889
25.8%
6 28052632
19.4%
0 25205595
17.4%
7 13259868
 
9.2%
2 13250388
 
9.2%
. 12039864
 
8.3%
5 5265686
 
3.6%
4 5202500
 
3.6%
3 2440907
 
1.7%
8 1214301
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144478368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37332889
25.8%
6 28052632
19.4%
0 25205595
17.4%
7 13259868
 
9.2%
2 13250388
 
9.2%
. 12039864
 
8.3%
5 5265686
 
3.6%
4 5202500
 
3.6%
3 2440907
 
1.7%
8 1214301
 
0.8%

player1_team_city
Text

MISSING 

Distinct34
Distinct (%)< 0.1%
Missing1187147
Missing (%)9.0%
Memory size100.9 MiB
2023-06-27T19:16:22.186977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length12
Mean length8.269233108
Min length2

Characters and Unicode

Total characters99560442
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHouston
2nd rowSacramento
3rd rowHouston
4th rowHouston
5th rowHouston
ValueCountFrequency (%)
new 960395
 
6.5%
los 707322
 
4.8%
angeles 707322
 
4.8%
state 413778
 
2.8%
golden 413778
 
2.8%
denver 413124
 
2.8%
philadelphia 411972
 
2.8%
boston 411430
 
2.8%
sacramento 408581
 
2.8%
washington 408263
 
2.8%
Other values (29) 9524073
64.4%
2023-06-27T19:16:22.404459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 9978594
 
10.0%
e 9633927
 
9.7%
o 9407126
 
9.4%
n 9376785
 
9.4%
t 7442042
 
7.5%
l 6460827
 
6.5%
i 5434759
 
5.5%
s 4342574
 
4.4%
r 3984106
 
4.0%
h 3402049
 
3.4%
Other values (32) 30097653
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 81866186
82.2%
Uppercase Letter 14922317
 
15.0%
Space Separator 2740174
 
2.8%
Other Punctuation 31765
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 9978594
12.2%
e 9633927
11.8%
o 9407126
11.5%
n 9376785
11.5%
t 7442042
9.1%
l 6460827
7.9%
i 5434759
6.6%
s 4342574
 
5.3%
r 3984106
 
4.9%
h 3402049
 
4.2%
Other values (11) 12403397
15.2%
Uppercase Letter
ValueCountFrequency (%)
A 1626932
10.9%
M 1534676
10.3%
C 1428713
9.6%
S 1413249
9.5%
P 1221053
 
8.2%
D 1216234
 
8.2%
O 971264
 
6.5%
N 960395
 
6.4%
L 817836
 
5.5%
B 568765
 
3.8%
Other values (9) 3163200
21.2%
Space Separator
ValueCountFrequency (%)
2740174
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 31765
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 96788503
97.2%
Common 2771939
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 9978594
 
10.3%
e 9633927
 
10.0%
o 9407126
 
9.7%
n 9376785
 
9.7%
t 7442042
 
7.7%
l 6460827
 
6.7%
i 5434759
 
5.6%
s 4342574
 
4.5%
r 3984106
 
4.1%
h 3402049
 
3.5%
Other values (30) 27325714
28.2%
Common
ValueCountFrequency (%)
2740174
98.9%
/ 31765
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99560442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 9978594
 
10.0%
e 9633927
 
9.7%
o 9407126
 
9.4%
n 9376785
 
9.4%
t 7442042
 
7.5%
l 6460827
 
6.5%
i 5434759
 
5.5%
s 4342574
 
4.4%
r 3984106
 
4.0%
h 3402049
 
3.4%
Other values (32) 30097653
30.2%

player1_team_nickname
Text

MISSING 

Distinct33
Distinct (%)< 0.1%
Missing1187147
Missing (%)9.0%
Memory size100.9 MiB
2023-06-27T19:16:22.572342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.735269601
Min length4

Characters and Unicode

Total characters81091730
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRockets
2nd rowKings
3rd rowRockets
4th rowRockets
5th rowRockets
ValueCountFrequency (%)
warriors 413778
 
3.3%
lakers 413506
 
3.3%
nuggets 413124
 
3.3%
76ers 411972
 
3.3%
celtics 411430
 
3.3%
kings 408581
 
3.3%
pacers 407595
 
3.3%
nets 407526
 
3.3%
suns 407475
 
3.3%
mavericks 406955
 
3.3%
Other values (24) 8339528
67.0%
2023-06-27T19:16:22.791627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 11008865
 
13.6%
r 7287952
 
9.0%
e 7039991
 
8.7%
i 5981707
 
7.4%
a 5955382
 
7.3%
l 3813129
 
4.7%
t 3381479
 
4.2%
c 3324168
 
4.1%
o 2742992
 
3.4%
n 2542362
 
3.1%
Other values (28) 28013703
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67649996
83.4%
Uppercase Letter 12216184
 
15.1%
Decimal Number 823944
 
1.0%
Space Separator 401606
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 11008865
16.3%
r 7287952
10.8%
e 7039991
10.4%
i 5981707
8.8%
a 5955382
8.8%
l 3813129
 
5.6%
t 3381479
 
5.0%
c 3324168
 
4.9%
o 2742992
 
4.1%
n 2542362
 
3.8%
Other values (11) 14571969
21.5%
Uppercase Letter
ValueCountFrequency (%)
B 1384351
11.3%
C 1219047
10.0%
S 1185051
9.7%
H 1179233
9.7%
T 1027833
8.4%
P 947204
7.8%
N 820650
6.7%
M 810790
 
6.6%
R 806087
 
6.6%
W 805943
 
6.6%
Other values (4) 2029995
16.6%
Decimal Number
ValueCountFrequency (%)
6 411972
50.0%
7 411972
50.0%
Space Separator
ValueCountFrequency (%)
401606
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79866180
98.5%
Common 1225550
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 11008865
13.8%
r 7287952
 
9.1%
e 7039991
 
8.8%
i 5981707
 
7.5%
a 5955382
 
7.5%
l 3813129
 
4.8%
t 3381479
 
4.2%
c 3324168
 
4.2%
o 2742992
 
3.4%
n 2542362
 
3.2%
Other values (25) 26788153
33.5%
Common
ValueCountFrequency (%)
6 411972
33.6%
7 411972
33.6%
401606
32.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81091730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 11008865
 
13.6%
r 7287952
 
9.0%
e 7039991
 
8.7%
i 5981707
 
7.4%
a 5955382
 
7.3%
l 3813129
 
4.7%
t 3381479
 
4.2%
c 3324168
 
4.1%
o 2742992
 
3.4%
n 2542362
 
3.1%
Other values (28) 28013703
34.5%
Distinct36
Distinct (%)< 0.1%
Missing1187147
Missing (%)9.0%
Memory size100.9 MiB
2023-06-27T19:16:22.939915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters36119592
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHOU
2nd rowSAC
3rd rowHOU
4th rowHOU
5th rowHOU
ValueCountFrequency (%)
gsw 413778
 
3.4%
lal 413506
 
3.4%
den 413124
 
3.4%
phi 411972
 
3.4%
bos 411430
 
3.4%
sac 408581
 
3.4%
was 408263
 
3.4%
ind 407595
 
3.4%
phx 407475
 
3.4%
dal 406955
 
3.4%
Other values (26) 7937185
65.9%
2023-06-27T19:16:23.130899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 4190258
11.6%
L 3256558
 
9.0%
N 2665874
 
7.4%
S 2637146
 
7.3%
O 2558622
 
7.1%
I 2427303
 
6.7%
H 2220885
 
6.1%
C 2209859
 
6.1%
M 1865298
 
5.2%
E 1729874
 
4.8%
Other values (13) 10357915
28.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 36119592
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 4190258
11.6%
L 3256558
 
9.0%
N 2665874
 
7.4%
S 2637146
 
7.3%
O 2558622
 
7.1%
I 2427303
 
6.7%
H 2220885
 
6.1%
C 2209859
 
6.1%
M 1865298
 
5.2%
E 1729874
 
4.8%
Other values (13) 10357915
28.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 36119592
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 4190258
11.6%
L 3256558
 
9.0%
N 2665874
 
7.4%
S 2637146
 
7.3%
O 2558622
 
7.1%
I 2427303
 
6.7%
H 2220885
 
6.1%
C 2209859
 
6.1%
M 1865298
 
5.2%
E 1729874
 
4.8%
Other values (13) 10357915
28.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36119592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 4190258
11.6%
L 3256558
 
9.0%
N 2665874
 
7.4%
S 2637146
 
7.3%
O 2558622
 
7.1%
I 2427303
 
6.7%
H 2220885
 
6.1%
C 2209859
 
6.1%
M 1865298
 
5.2%
E 1729874
 
4.8%
Other values (13) 10357915
28.7%

person2type
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.292807574
Minimum0
Maximum7
Zeros9429986
Zeros (%)71.3%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:23.190161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.054918664
Coefficient of variation (CV)1.589500793
Kurtosis-0.9275261854
Mean1.292807574
Median Absolute Deviation (MAD)0
Skewness0.997151904
Sum17099980
Variance4.222690717
MonotonicityNot monotonic
2023-06-27T19:16:23.231938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 9429986
71.3%
5 1911895
 
14.5%
4 1884716
 
14.2%
3 310
 
< 0.1%
7 99
 
< 0.1%
2 3
 
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
0 9429986
71.3%
2 3
 
< 0.1%
3 310
 
< 0.1%
4 1884716
 
14.2%
5 1911895
 
14.5%
ValueCountFrequency (%)
7 99
 
< 0.1%
6 2
 
< 0.1%
5 1911895
14.5%
4 1884716
14.2%
3 310
 
< 0.1%
Distinct2528
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:23.530614image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.123432271
Min length1

Characters and Unicode

Total characters28086662
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row178
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 9453901
71.5%
2544 20260
 
0.2%
101108 19529
 
0.1%
201566 16191
 
0.1%
467 15431
 
0.1%
959 14619
 
0.1%
977 14361
 
0.1%
201935 14163
 
0.1%
1889 14037
 
0.1%
2548 12833
 
0.1%
Other values (2518) 3631686
 
27.5%
2023-06-27T19:16:23.866588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12092525
43.1%
2 3550903
 
12.6%
1 3057751
 
10.9%
6 1566912
 
5.6%
3 1466717
 
5.2%
7 1416645
 
5.0%
9 1415639
 
5.0%
5 1244331
 
4.4%
4 1178450
 
4.2%
8 1096789
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28086662
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12092525
43.1%
2 3550903
 
12.6%
1 3057751
 
10.9%
6 1566912
 
5.6%
3 1466717
 
5.2%
7 1416645
 
5.0%
9 1415639
 
5.0%
5 1244331
 
4.4%
4 1178450
 
4.2%
8 1096789
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 28086662
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12092525
43.1%
2 3550903
 
12.6%
1 3057751
 
10.9%
6 1566912
 
5.6%
3 1466717
 
5.2%
7 1416645
 
5.0%
9 1415639
 
5.0%
5 1244331
 
4.4%
4 1178450
 
4.2%
8 1096789
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28086662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12092525
43.1%
2 3550903
 
12.6%
1 3057751
 
10.9%
6 1566912
 
5.6%
3 1466717
 
5.2%
7 1416645
 
5.0%
9 1415639
 
5.0%
5 1244331
 
4.4%
4 1178450
 
4.2%
8 1096789
 
3.9%

player2_name
Text

MISSING 

Distinct2498
Distinct (%)0.1%
Missing9454004
Missing (%)71.5%
Memory size100.9 MiB
2023-06-27T19:16:24.184036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.75220931
Min length4

Characters and Unicode

Total characters48114175
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)< 0.1%

Sample

1st rowOlden Polynice
2nd rowHakeem Olajuwon
3rd rowClyde Drexler
4th rowOlden Polynice
5th rowMitch Richmond
ValueCountFrequency (%)
williams 78158
 
1.0%
chris 70867
 
0.9%
james 56535
 
0.7%
jason 55846
 
0.7%
anthony 52531
 
0.7%
kevin 49932
 
0.7%
paul 49052
 
0.6%
johnson 46113
 
0.6%
mike 43168
 
0.6%
davis 40039
 
0.5%
Other values (2717) 7071000
92.9%
2023-06-27T19:16:24.594173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4077754
 
8.5%
a 3897208
 
8.1%
3840234
 
8.0%
n 3540283
 
7.4%
r 3469854
 
7.2%
o 3202588
 
6.7%
i 2767688
 
5.8%
l 2380384
 
4.9%
s 2073834
 
4.3%
t 1404736
 
2.9%
Other values (46) 17459612
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36093926
75.0%
Uppercase Letter 7955868
 
16.5%
Space Separator 3840234
 
8.0%
Other Punctuation 182309
 
0.4%
Dash Punctuation 41838
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4077754
11.3%
a 3897208
10.8%
n 3540283
9.8%
r 3469854
9.6%
o 3202588
 
8.9%
i 2767688
 
7.7%
l 2380384
 
6.6%
s 2073834
 
5.7%
t 1404736
 
3.9%
d 1167004
 
3.2%
Other values (16) 8112593
22.5%
Uppercase Letter
ValueCountFrequency (%)
J 831674
 
10.5%
M 693544
 
8.7%
D 630931
 
7.9%
B 603040
 
7.6%
C 509155
 
6.4%
A 491915
 
6.2%
S 464950
 
5.8%
R 456612
 
5.7%
T 395882
 
5.0%
G 361689
 
4.5%
Other values (16) 2516476
31.6%
Other Punctuation
ValueCountFrequency (%)
. 137192
75.3%
' 45117
 
24.7%
Space Separator
ValueCountFrequency (%)
3840234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41838
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44049794
91.6%
Common 4064381
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4077754
 
9.3%
a 3897208
 
8.8%
n 3540283
 
8.0%
r 3469854
 
7.9%
o 3202588
 
7.3%
i 2767688
 
6.3%
l 2380384
 
5.4%
s 2073834
 
4.7%
t 1404736
 
3.2%
d 1167004
 
2.6%
Other values (42) 16068461
36.5%
Common
ValueCountFrequency (%)
3840234
94.5%
. 137192
 
3.4%
' 45117
 
1.1%
- 41838
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48114175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4077754
 
8.5%
a 3897208
 
8.1%
3840234
 
8.0%
n 3540283
 
7.4%
r 3469854
 
7.2%
o 3202588
 
6.7%
i 2767688
 
5.8%
l 2380384
 
4.9%
s 2073834
 
4.3%
t 1404736
 
2.9%
Other values (46) 17459612
36.3%

player2_team_id
Text

MISSING 

Distinct30
Distinct (%)< 0.1%
Missing9430400
Missing (%)71.3%
Memory size100.9 MiB
2023-06-27T19:16:24.802941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters45559332
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1610612758.0
2nd row1610612745.0
3rd row1610612745.0
4th row1610612758.0
5th row1610612758.0
ValueCountFrequency (%)
1610612738.0 135306
 
3.6%
1610612759.0 134154
 
3.5%
1610612755.0 132632
 
3.5%
1610612742.0 131663
 
3.5%
1610612743.0 130999
 
3.5%
1610612744.0 129913
 
3.4%
1610612762.0 129902
 
3.4%
1610612751.0 129901
 
3.4%
1610612763.0 129768
 
3.4%
1610612754.0 129708
 
3.4%
Other values (20) 2482665
65.4%
2023-06-27T19:16:25.041644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11770014
25.8%
6 8844957
19.4%
0 7949728
17.4%
2 4177569
 
9.2%
7 4177395
 
9.2%
. 3796611
 
8.3%
5 1654562
 
3.6%
4 1636601
 
3.6%
3 775552
 
1.7%
9 389392
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41762721
91.7%
Other Punctuation 3796611
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11770014
28.2%
6 8844957
21.2%
0 7949728
19.0%
2 4177569
 
10.0%
7 4177395
 
10.0%
5 1654562
 
4.0%
4 1636601
 
3.9%
3 775552
 
1.9%
9 389392
 
0.9%
8 386951
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 3796611
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45559332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11770014
25.8%
6 8844957
19.4%
0 7949728
17.4%
2 4177569
 
9.2%
7 4177395
 
9.2%
. 3796611
 
8.3%
5 1654562
 
3.6%
4 1636601
 
3.6%
3 775552
 
1.7%
9 389392
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45559332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11770014
25.8%
6 8844957
19.4%
0 7949728
17.4%
2 4177569
 
9.2%
7 4177395
 
9.2%
. 3796611
 
8.3%
5 1654562
 
3.6%
4 1636601
 
3.6%
3 775552
 
1.7%
9 389392
 
0.9%

player2_team_city
Text

MISSING 

Distinct34
Distinct (%)< 0.1%
Missing9430400
Missing (%)71.3%
Memory size100.9 MiB
2023-06-27T19:16:25.193280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length12
Mean length8.264009929
Min length2

Characters and Unicode

Total characters31375231
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSacramento
2nd rowHouston
3rd rowHouston
4th rowSacramento
5th rowSacramento
ValueCountFrequency (%)
new 296874
 
6.4%
los 213452
 
4.6%
angeles 213452
 
4.6%
boston 135306
 
2.9%
san 134154
 
2.9%
antonio 134154
 
2.9%
philadelphia 132632
 
2.8%
dallas 131663
 
2.8%
denver 130999
 
2.8%
golden 129913
 
2.8%
Other values (29) 3003491
64.5%
2023-06-27T19:16:25.404833image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3164412
 
10.1%
e 2997610
 
9.6%
n 2964347
 
9.4%
o 2960091
 
9.4%
t 2338734
 
7.5%
l 2045194
 
6.5%
i 1734019
 
5.5%
s 1359451
 
4.3%
r 1242359
 
4.0%
h 1092609
 
3.5%
Other values (32) 9476405
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25799581
82.2%
Uppercase Letter 4705870
 
15.0%
Space Separator 859479
 
2.7%
Other Punctuation 10301
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3164412
12.3%
e 2997610
11.6%
n 2964347
11.5%
o 2960091
11.5%
t 2338734
9.1%
l 2045194
7.9%
i 1734019
6.7%
s 1359451
 
5.3%
r 1242359
 
4.8%
h 1092609
 
4.2%
Other values (11) 3900755
15.1%
Uppercase Letter
ValueCountFrequency (%)
A 515757
11.0%
M 491655
10.4%
C 457333
9.7%
S 442261
9.4%
P 386401
 
8.2%
D 384047
 
8.2%
O 311823
 
6.6%
N 296874
 
6.3%
L 252931
 
5.4%
B 190567
 
4.0%
Other values (9) 976221
20.7%
Space Separator
ValueCountFrequency (%)
859479
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 10301
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30505451
97.2%
Common 869780
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3164412
 
10.4%
e 2997610
 
9.8%
n 2964347
 
9.7%
o 2960091
 
9.7%
t 2338734
 
7.7%
l 2045194
 
6.7%
i 1734019
 
5.7%
s 1359451
 
4.5%
r 1242359
 
4.1%
h 1092609
 
3.6%
Other values (30) 8606625
28.2%
Common
ValueCountFrequency (%)
859479
98.8%
/ 10301
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31375231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3164412
 
10.1%
e 2997610
 
9.6%
n 2964347
 
9.4%
o 2960091
 
9.4%
t 2338734
 
7.5%
l 2045194
 
6.5%
i 1734019
 
5.5%
s 1359451
 
4.3%
r 1242359
 
4.0%
h 1092609
 
3.5%
Other values (32) 9476405
30.2%

player2_team_nickname
Text

MISSING 

Distinct33
Distinct (%)< 0.1%
Missing9430400
Missing (%)71.3%
Memory size100.9 MiB
2023-06-27T19:16:25.564167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.724575154
Min length4

Characters and Unicode

Total characters25530596
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKings
2nd rowRockets
3rd rowRockets
4th rowKings
5th rowKings
ValueCountFrequency (%)
celtics 135306
 
3.5%
spurs 134154
 
3.4%
76ers 132632
 
3.4%
mavericks 131663
 
3.4%
nuggets 130999
 
3.3%
warriors 129913
 
3.3%
jazz 129902
 
3.3%
nets 129901
 
3.3%
grizzlies 129768
 
3.3%
pacers 129708
 
3.3%
Other values (24) 2607269
66.5%
2023-06-27T19:16:25.798490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 3464619
 
13.6%
r 2295166
 
9.0%
e 2227107
 
8.7%
a 1878995
 
7.4%
i 1876139
 
7.3%
l 1206438
 
4.7%
t 1066129
 
4.2%
c 1046015
 
4.1%
o 848966
 
3.3%
n 791950
 
3.1%
Other values (28) 8829072
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21300802
83.4%
Uppercase Letter 3839926
 
15.0%
Decimal Number 265264
 
1.0%
Space Separator 124604
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 3464619
16.3%
r 2295166
10.8%
e 2227107
10.5%
a 1878995
8.8%
i 1876139
8.8%
l 1206438
 
5.7%
t 1066129
 
5.0%
c 1046015
 
4.9%
o 848966
 
4.0%
n 791950
 
3.7%
Other values (11) 4599278
21.6%
Uppercase Letter
ValueCountFrequency (%)
B 437036
11.4%
C 387640
10.1%
H 372019
9.7%
S 366005
9.5%
T 326926
8.5%
P 301568
7.9%
N 260900
6.8%
M 255559
6.7%
W 251816
 
6.6%
R 247035
 
6.4%
Other values (4) 633422
16.5%
Decimal Number
ValueCountFrequency (%)
6 132632
50.0%
7 132632
50.0%
Space Separator
ValueCountFrequency (%)
124604
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25140728
98.5%
Common 389868
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 3464619
13.8%
r 2295166
 
9.1%
e 2227107
 
8.9%
a 1878995
 
7.5%
i 1876139
 
7.5%
l 1206438
 
4.8%
t 1066129
 
4.2%
c 1046015
 
4.2%
o 848966
 
3.4%
n 791950
 
3.2%
Other values (25) 8439204
33.6%
Common
ValueCountFrequency (%)
6 132632
34.0%
7 132632
34.0%
124604
32.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25530596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 3464619
 
13.6%
r 2295166
 
9.0%
e 2227107
 
8.7%
a 1878995
 
7.4%
i 1876139
 
7.3%
l 1206438
 
4.7%
t 1066129
 
4.2%
c 1046015
 
4.1%
o 848966
 
3.3%
n 791950
 
3.1%
Other values (28) 8829072
34.6%
Distinct36
Distinct (%)< 0.1%
Missing9430400
Missing (%)71.3%
Memory size100.9 MiB
2023-06-27T19:16:25.939618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters11389833
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSAC
2nd rowHOU
3rd rowHOU
4th rowSAC
5th rowSAC
ValueCountFrequency (%)
bos 135306
 
3.6%
sas 134154
 
3.5%
phi 132632
 
3.5%
dal 131663
 
3.5%
den 130999
 
3.5%
gsw 129913
 
3.4%
uta 129902
 
3.4%
ind 129708
 
3.4%
phx 129165
 
3.4%
atl 128672
 
3.4%
Other values (26) 2484497
65.4%
2023-06-27T19:16:26.130569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1322799
11.6%
L 1019908
 
9.0%
S 838580
 
7.4%
N 833790
 
7.3%
O 808467
 
7.1%
I 768947
 
6.8%
C 699306
 
6.1%
H 694430
 
6.1%
M 602652
 
5.3%
E 541635
 
4.8%
Other values (13) 3259319
28.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 11389833
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1322799
11.6%
L 1019908
 
9.0%
S 838580
 
7.4%
N 833790
 
7.3%
O 808467
 
7.1%
I 768947
 
6.8%
C 699306
 
6.1%
H 694430
 
6.1%
M 602652
 
5.3%
E 541635
 
4.8%
Other values (13) 3259319
28.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 11389833
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1322799
11.6%
L 1019908
 
9.0%
S 838580
 
7.4%
N 833790
 
7.3%
O 808467
 
7.1%
I 768947
 
6.8%
C 699306
 
6.1%
H 694430
 
6.1%
M 602652
 
5.3%
E 541635
 
4.8%
Other values (13) 3259319
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11389833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1322799
11.6%
L 1019908
 
9.0%
S 838580
 
7.4%
N 833790
 
7.3%
O 808467
 
7.1%
I 768947
 
6.8%
C 699306
 
6.1%
H 694430
 
6.1%
M 602652
 
5.3%
E 541635
 
4.8%
Other values (13) 3259319
28.6%

person3type
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2244216021
Minimum0
Maximum5
Zeros11439649
Zeros (%)86.5%
Negative0
Negative (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:26.193536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7612069409
Coefficient of variation (CV)3.391861272
Kurtosis24.11749213
Mean0.2244216021
Median Absolute Deviation (MAD)0
Skewness4.742873955
Sum2968427
Variance0.5794360068
MonotonicityNot monotonic
2023-06-27T19:16:26.238904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 11439649
86.5%
1 1445940
 
10.9%
4 178132
 
1.3%
5 160713
 
1.2%
2 1337
 
< 0.1%
3 1240
 
< 0.1%
ValueCountFrequency (%)
0 11439649
86.5%
1 1445940
 
10.9%
2 1337
 
< 0.1%
3 1240
 
< 0.1%
4 178132
 
1.3%
ValueCountFrequency (%)
5 160713
 
1.2%
4 178132
 
1.3%
3 1240
 
< 0.1%
2 1337
 
< 0.1%
1 1445940
10.9%
Distinct2255
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:26.521494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length1
Mean length1.096192859
Min length1

Characters and Unicode

Total characters14499355
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row722
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 12890478
97.5%
1495 3049
 
< 0.1%
948 2287
 
< 0.1%
1112 2120
 
< 0.1%
2730 2045
 
< 0.1%
708 1989
 
< 0.1%
2200 1879
 
< 0.1%
406 1875
 
< 0.1%
1882 1874
 
< 0.1%
689 1796
 
< 0.1%
Other values (2245) 317619
 
2.4%
2023-06-27T19:16:26.836468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13113221
90.4%
2 303055
 
2.1%
1 269203
 
1.9%
6 134976
 
0.9%
9 125727
 
0.9%
7 124416
 
0.9%
3 122902
 
0.8%
5 107187
 
0.7%
4 105140
 
0.7%
8 93528
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14499355
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13113221
90.4%
2 303055
 
2.1%
1 269203
 
1.9%
6 134976
 
0.9%
9 125727
 
0.9%
7 124416
 
0.9%
3 122902
 
0.8%
5 107187
 
0.7%
4 105140
 
0.7%
8 93528
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 14499355
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13113221
90.4%
2 303055
 
2.1%
1 269203
 
1.9%
6 134976
 
0.9%
9 125727
 
0.9%
7 124416
 
0.9%
3 122902
 
0.8%
5 107187
 
0.7%
4 105140
 
0.7%
8 93528
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14499355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13113221
90.4%
2 303055
 
2.1%
1 269203
 
1.9%
6 134976
 
0.9%
9 125727
 
0.9%
7 124416
 
0.9%
3 122902
 
0.8%
5 107187
 
0.7%
4 105140
 
0.7%
8 93528
 
0.6%

player3_name
Text

MISSING 

Distinct2215
Distinct (%)0.7%
Missing12893043
Missing (%)97.5%
Memory size100.9 MiB
2023-06-27T19:16:27.138385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.85000659
Min length4

Characters and Unicode

Total characters4291491
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)< 0.1%

Sample

1st rowCorliss Williamson
2nd rowMitch Richmond
3rd rowMahmoud Abdul-Rauf
4th rowMitch Richmond
5th rowDuane Causwell
ValueCountFrequency (%)
chris 7122
 
1.1%
williams 5510
 
0.8%
kevin 4631
 
0.7%
davis 4586
 
0.7%
wallace 4574
 
0.7%
johnson 4373
 
0.6%
smith 4350
 
0.6%
anthony 4228
 
0.6%
james 4076
 
0.6%
jason 3767
 
0.6%
Other values (2490) 625762
93.0%
2023-06-27T19:16:27.524639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 362886
 
8.5%
a 358133
 
8.3%
339011
 
7.9%
n 309488
 
7.2%
r 296557
 
6.9%
o 275576
 
6.4%
i 251717
 
5.9%
l 211236
 
4.9%
s 179297
 
4.2%
t 131301
 
3.1%
Other values (46) 1576289
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3227849
75.2%
Uppercase Letter 705048
 
16.4%
Space Separator 339011
 
7.9%
Other Punctuation 15755
 
0.4%
Dash Punctuation 3828
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 362886
11.2%
a 358133
11.1%
n 309488
9.6%
r 296557
 
9.2%
o 275576
 
8.5%
i 251717
 
7.8%
l 211236
 
6.5%
s 179297
 
5.6%
t 131301
 
4.1%
d 105850
 
3.3%
Other values (16) 745808
23.1%
Uppercase Letter
ValueCountFrequency (%)
J 65063
 
9.2%
M 62493
 
8.9%
D 57975
 
8.2%
B 51233
 
7.3%
A 47687
 
6.8%
C 42910
 
6.1%
S 42291
 
6.0%
R 37566
 
5.3%
T 35410
 
5.0%
G 34876
 
4.9%
Other values (16) 227544
32.3%
Other Punctuation
ValueCountFrequency (%)
. 9170
58.2%
' 6585
41.8%
Space Separator
ValueCountFrequency (%)
339011
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3828
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3932897
91.6%
Common 358594
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 362886
 
9.2%
a 358133
 
9.1%
n 309488
 
7.9%
r 296557
 
7.5%
o 275576
 
7.0%
i 251717
 
6.4%
l 211236
 
5.4%
s 179297
 
4.6%
t 131301
 
3.3%
d 105850
 
2.7%
Other values (42) 1450856
36.9%
Common
ValueCountFrequency (%)
339011
94.5%
. 9170
 
2.6%
' 6585
 
1.8%
- 3828
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4291491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 362886
 
8.5%
a 358133
 
8.3%
339011
 
7.9%
n 309488
 
7.2%
r 296557
 
6.9%
o 275576
 
6.4%
i 251717
 
5.9%
l 211236
 
4.9%
s 179297
 
4.2%
t 131301
 
3.1%
Other values (46) 1576289
36.7%

player3_team_id
Text

MISSING 

Distinct30
Distinct (%)< 0.1%
Missing12888166
Missing (%)97.4%
Memory size100.9 MiB
2023-06-27T19:16:27.717492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters4066140
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1610612758.0
2nd row1610612758.0
3rd row1610612745.0
4th row1610612758.0
5th row1610612758.0
ValueCountFrequency (%)
1610612759.0 12874
 
3.8%
1610612747.0 12463
 
3.7%
1610612743.0 12274
 
3.6%
1610612762.0 12143
 
3.6%
1610612746.0 12055
 
3.6%
1610612763.0 12006
 
3.5%
1610612754.0 11973
 
3.5%
1610612744.0 11753
 
3.5%
1610612748.0 11692
 
3.5%
1610612761.0 11622
 
3.4%
Other values (20) 217990
64.3%
2023-06-27T19:16:27.961308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1050255
25.8%
6 791687
19.5%
0 708993
17.4%
7 374275
 
9.2%
2 372233
 
9.2%
. 338845
 
8.3%
4 147756
 
3.6%
5 146438
 
3.6%
3 68353
 
1.7%
9 34725
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3727295
91.7%
Other Punctuation 338845
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1050255
28.2%
6 791687
21.2%
0 708993
19.0%
7 374275
 
10.0%
2 372233
 
10.0%
4 147756
 
4.0%
5 146438
 
3.9%
3 68353
 
1.8%
9 34725
 
0.9%
8 32580
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 338845
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4066140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1050255
25.8%
6 791687
19.5%
0 708993
17.4%
7 374275
 
9.2%
2 372233
 
9.2%
. 338845
 
8.3%
4 147756
 
3.6%
5 146438
 
3.6%
3 68353
 
1.7%
9 34725
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4066140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1050255
25.8%
6 791687
19.5%
0 708993
17.4%
7 374275
 
9.2%
2 372233
 
9.2%
. 338845
 
8.3%
4 147756
 
3.6%
5 146438
 
3.6%
3 68353
 
1.7%
9 34725
 
0.9%

player3_team_city
Text

MISSING 

Distinct34
Distinct (%)< 0.1%
Missing12888166
Missing (%)97.4%
Memory size100.9 MiB
2023-06-27T19:16:28.119420image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length12
Mean length8.273110124
Min length2

Characters and Unicode

Total characters2803302
Distinct characters42
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSacramento
2nd rowSacramento
3rd rowHouston
4th rowSacramento
5th rowSacramento
ValueCountFrequency (%)
new 24896
 
6.0%
los 21683
 
5.2%
angeles 21683
 
5.2%
antonio 12874
 
3.1%
san 12874
 
3.1%
denver 12274
 
2.9%
utah 12143
 
2.9%
indiana 11973
 
2.9%
golden 11753
 
2.8%
state 11753
 
2.8%
Other values (29) 263653
63.1%
2023-06-27T19:16:28.330556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 280064
 
10.0%
e 269652
 
9.6%
n 267300
 
9.5%
o 264953
 
9.5%
t 209654
 
7.5%
l 181232
 
6.5%
i 155698
 
5.6%
s 123750
 
4.4%
r 109537
 
3.9%
h 96615
 
3.4%
Other values (32) 844847
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2302634
82.1%
Uppercase Letter 421174
 
15.0%
Space Separator 78714
 
2.8%
Other Punctuation 780
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 280064
12.2%
e 269652
11.7%
n 267300
11.6%
o 264953
11.5%
t 209654
9.1%
l 181232
7.9%
i 155698
6.8%
s 123750
 
5.4%
r 109537
 
4.8%
h 96615
 
4.2%
Other values (11) 344179
14.9%
Uppercase Letter
ValueCountFrequency (%)
A 48831
11.6%
M 43994
10.4%
C 40236
9.6%
S 39648
9.4%
D 34802
 
8.3%
P 34376
 
8.2%
O 26802
 
6.4%
N 24896
 
5.9%
L 24518
 
5.8%
B 14881
 
3.5%
Other values (9) 88190
20.9%
Space Separator
ValueCountFrequency (%)
78714
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 780
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2723808
97.2%
Common 79494
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 280064
 
10.3%
e 269652
 
9.9%
n 267300
 
9.8%
o 264953
 
9.7%
t 209654
 
7.7%
l 181232
 
6.7%
i 155698
 
5.7%
s 123750
 
4.5%
r 109537
 
4.0%
h 96615
 
3.5%
Other values (30) 765353
28.1%
Common
ValueCountFrequency (%)
78714
99.0%
/ 780
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2803302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 280064
 
10.0%
e 269652
 
9.6%
n 267300
 
9.5%
o 264953
 
9.5%
t 209654
 
7.5%
l 181232
 
6.5%
i 155698
 
5.6%
s 123750
 
4.4%
r 109537
 
3.9%
h 96615
 
3.4%
Other values (32) 844847
30.1%

player3_team_nickname
Text

MISSING 

Distinct33
Distinct (%)< 0.1%
Missing12888166
Missing (%)97.4%
Memory size100.9 MiB
2023-06-27T19:16:28.519801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.737959834
Min length4

Characters and Unicode

Total characters2283124
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKings
2nd rowKings
3rd rowRockets
4th rowKings
5th rowKings
ValueCountFrequency (%)
spurs 12874
 
3.7%
lakers 12463
 
3.6%
nuggets 12274
 
3.5%
jazz 12143
 
3.5%
clippers 12055
 
3.4%
grizzlies 12006
 
3.4%
pacers 11973
 
3.4%
warriors 11753
 
3.4%
heat 11692
 
3.3%
raptors 11622
 
3.3%
Other values (24) 229518
65.5%
2023-06-27T19:16:28.746188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 308467
 
13.5%
r 208685
 
9.1%
e 199844
 
8.8%
a 169059
 
7.4%
i 165115
 
7.2%
l 107860
 
4.7%
t 95000
 
4.2%
c 90378
 
4.0%
o 76881
 
3.4%
u 70873
 
3.1%
Other values (28) 790962
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1904868
83.4%
Uppercase Letter 343722
 
15.1%
Decimal Number 23006
 
1.0%
Space Separator 11528
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 308467
16.2%
r 208685
11.0%
e 199844
10.5%
a 169059
8.9%
i 165115
8.7%
l 107860
 
5.7%
t 95000
 
5.0%
c 90378
 
4.7%
o 76881
 
4.0%
u 70873
 
3.7%
Other values (11) 412706
21.7%
Uppercase Letter
ValueCountFrequency (%)
B 38864
11.3%
S 33923
9.9%
C 33678
9.8%
H 33492
9.7%
T 29696
8.6%
P 27143
7.9%
N 23136
6.7%
R 22743
6.6%
M 22343
 
6.5%
W 22010
 
6.4%
Other values (4) 56694
16.5%
Decimal Number
ValueCountFrequency (%)
7 11503
50.0%
6 11503
50.0%
Space Separator
ValueCountFrequency (%)
11528
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2248590
98.5%
Common 34534
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 308467
13.7%
r 208685
 
9.3%
e 199844
 
8.9%
a 169059
 
7.5%
i 165115
 
7.3%
l 107860
 
4.8%
t 95000
 
4.2%
c 90378
 
4.0%
o 76881
 
3.4%
u 70873
 
3.2%
Other values (25) 756428
33.6%
Common
ValueCountFrequency (%)
11528
33.4%
7 11503
33.3%
6 11503
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2283124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 308467
 
13.5%
r 208685
 
9.1%
e 199844
 
8.8%
a 169059
 
7.4%
i 165115
 
7.2%
l 107860
 
4.7%
t 95000
 
4.2%
c 90378
 
4.0%
o 76881
 
3.4%
u 70873
 
3.1%
Other values (28) 790962
34.6%
Distinct36
Distinct (%)< 0.1%
Missing12888166
Missing (%)97.4%
Memory size100.9 MiB
2023-06-27T19:16:28.893424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1016535
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSAC
2nd rowSAC
3rd rowHOU
4th rowSAC
5th rowSAC
ValueCountFrequency (%)
sas 12874
 
3.8%
lal 12463
 
3.7%
den 12274
 
3.6%
uta 12143
 
3.6%
lac 12055
 
3.6%
ind 11973
 
3.5%
gsw 11753
 
3.5%
mia 11692
 
3.5%
tor 11622
 
3.4%
por 11528
 
3.4%
Other values (26) 218468
64.5%
2023-06-27T19:16:29.083708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 119812
11.8%
L 92614
 
9.1%
S 74115
 
7.3%
N 73536
 
7.2%
O 71012
 
7.0%
I 68791
 
6.8%
H 62082
 
6.1%
C 61680
 
6.1%
M 53909
 
5.3%
E 49141
 
4.8%
Other values (13) 289843
28.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1016535
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 119812
11.8%
L 92614
 
9.1%
S 74115
 
7.3%
N 73536
 
7.2%
O 71012
 
7.0%
I 68791
 
6.8%
H 62082
 
6.1%
C 61680
 
6.1%
M 53909
 
5.3%
E 49141
 
4.8%
Other values (13) 289843
28.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1016535
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 119812
11.8%
L 92614
 
9.1%
S 74115
 
7.3%
N 73536
 
7.2%
O 71012
 
7.0%
I 68791
 
6.8%
H 62082
 
6.1%
C 61680
 
6.1%
M 53909
 
5.3%
E 49141
 
4.8%
Other values (13) 289843
28.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1016535
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 119812
11.8%
L 92614
 
9.1%
S 74115
 
7.3%
N 73536
 
7.2%
O 71012
 
7.0%
I 68791
 
6.8%
H 62082
 
6.1%
C 61680
 
6.1%
M 53909
 
5.3%
E 49141
 
4.8%
Other values (13) 289843
28.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size100.9 MiB
2023-06-27T19:16:29.136061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters13227011
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 10091539
76.3%
1 3135472
 
23.7%
2023-06-27T19:16:29.246687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10091539
76.3%
1 3135472
 
23.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13227011
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10091539
76.3%
1 3135472
 
23.7%

Most occurring scripts

ValueCountFrequency (%)
Common 13227011
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10091539
76.3%
1 3135472
 
23.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13227011
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10091539
76.3%
1 3135472
 
23.7%